table (Transact-SQL)

Is a special data type that can be used to store a result set for processing at a later time. table is primarily used for temporary storage of a set of rows returned as the result set of a table-valued function. Functions and variables can be declared to be of type table. table variables can be used in functions, stored procedures, and batches. To declare variables of type table, use DECLARE @local_variable.

Is the same subset of information that is used to define a table in CREATE TABLE. The table declaration includes column definitions, names, data types, and constraints. The only constraint types allowed are PRIMARY KEY, UNIQUE KEY, and NULL.

Is the collation of the column that is made up of a Microsoft Windows locale and a comparison style, a Windows locale and the binary notation, or a Microsoft SQL Server collation. If collation_definition is not specified, the column inherits the collation of the current database. Or if the column is defined as a common language runtime (CLR) user-defined type, the column inherits the collation of the user-defined type.

table variables provide the following benefits for small-scale queries that have query plans that do not change and when recompilation concerns are dominant:

A table variable behaves like a local variable. It has a well-defined scope. This is the function, stored procedure, or batch that it is declared in.

Within its scope, a table variable can be used like a regular table. It may be applied anywhere a table or table expression is used in SELECT, INSERT, UPDATE, and DELETE statements. However, table cannot be used in the following statement:

Table variables does not have distribution statistics, theywill not trigger recompiles. Therefore, in many cases, the optimizer will build a query plan on the assumption that the table variable has no rows. For this reason, you should be cautious about using a table variable if you expect a larger number of rows (greater than 100). Temp tables may be a better solution in this case. Alternatively, for queries that join the table variable with other tables, use the RECOMPILE hint, which will cause the optimizer to use the correct cardinatlity for the table variable.

table variables are not supported in the SQL Server optimizer's cost-based reasoning model. Therefore, they should not be used when cost-based choices are required to achieve an efficient query plan. Temporary tables are preferred when cost-based choices are required. This typically includes queries with joins, parallelism decisions, and index selection choices.

Queries that modify table variables do not generate parallel query execution plans. Performance can be affected when very large table variables, or table variables in complex queries, are modified. In these situations, consider using temporary tables instead. For more information, see CREATE TABLE (Transact-SQL). Queries that read table variables without modifying them can still be parallelized.

Indexes cannot be created explicitly on table variables, and no statistics are kept on table variables. In some cases, performance may improve by using temporary tables instead, which support indexes and statistics. For more information about temporary tables, see CREATE TABLE (Transact-SQL).

A. Declaring a variable of type table

The following example creates a table variable that stores the values specified in the OUTPUT clause of the UPDATE statement. Two SELECT statements follow that return the values in @MyTableVar and the results of the update operation in the Employee table. Note that the results in the INSERTED.ModifiedDate column differ from the values in the ModifiedDate column in the Employee table. This is because the AFTER UPDATE trigger, which updates the value of ModifiedDate to the current date, is defined on the Employee table. However, the columns returned from OUTPUT reflect the data before triggers are fired. For more information, see OUTPUT Clause (Transact-SQL).

B. Creating an inline table-valued function

The following example returns an inline table-valued function. It returns three columns ProductID, Name and the aggregate of year-to-date totals by store as YTD Total for each product sold to the store.